Search engines are designed to crawl and gather data from information resources and index the data for quick retrieval. Search queries may be submitted and compared against the index to identify relevant information, which is provided in the form of search results. Various algorithms are used to improve the quality of search results. These algorithms may rank or weight search results in an attempt to reorder and return more relevant search results.
Click models are mathematical models used to infer a user's judgments on the relevance or irrelevance of specific search results. Click models may be part of learn-to-rank algorithms that attempt to learn to rank search results based in part on user behavior and interactions with search results. Current click models are not well-suited for electronic commerce (e-commerce) environments, where users interact with search results differently compared to search results returned by traditional search engines.